|
|
Absolute deviation, 绝对离差8 d( r, z: s3 e0 A6 c1 K
Absolute number, 绝对数
- h' i# w, a6 B6 s& `0 N( fAbsolute residuals, 绝对残差1 X Y2 h5 P1 X7 ^1 p6 T
Acceleration array, 加速度立体阵8 A! B, \; N1 z0 M, u% r
Acceleration in an arbitrary direction, 任意方向上的加速度% h, N: _- V+ K8 m9 \
Acceleration normal, 法向加速度
3 W0 n$ V1 a$ J7 j, _/ \ }Acceleration space dimension, 加速度空间的维数
' p! q$ ?9 X4 A$ D! j+ ^Acceleration tangential, 切向加速度
+ G2 S# O, b/ R$ {9 h$ \/ v, `Acceleration vector, 加速度向量" }* Q9 ~) z+ j
Acceptable hypothesis, 可接受假设
- i8 q D8 F) L9 T pAccumulation, 累积# B% j2 ^0 s7 [: ~! G; O" N
Accuracy, 准确度$ R+ a3 d1 F" B4 \1 W6 |
Actual frequency, 实际频数- j9 U; U( T3 O9 M
Adaptive estimator, 自适应估计量3 n' l- o, B# P8 ~0 o1 }8 ~) O& L. `0 F
Addition, 相加7 l4 J" k0 {* ]+ V o8 f9 t
Addition theorem, 加法定理2 u. y: H5 t' b/ _! m. ^$ N
Additivity, 可加性* Q; E$ x& X9 q* l7 L7 o
Adjusted rate, 调整率
7 }0 N4 u& z% e# ^Adjusted value, 校正值
" F8 B7 ?) L6 p$ W( {- ?Admissible error, 容许误差$ R7 w5 {0 }+ j% r" |# P5 i
Aggregation, 聚集性7 O1 K" M. }% E" {( I& ~
Alternative hypothesis, 备择假设5 a: {& }& g2 k( c7 `* E8 H
Among groups, 组间' q9 E# V8 C) X, x" I9 l' b- b
Amounts, 总量
2 f5 |+ f$ d) J& F* pAnalysis of correlation, 相关分析
& N# }, c3 {- b$ f, j0 C5 _ hAnalysis of covariance, 协方差分析
) v: T" v. E g: e" l0 m( b4 Y# @Analysis of regression, 回归分析
* M; k" Z. g8 ~9 W$ I- ?5 v2 lAnalysis of time series, 时间序列分析
, A# o' g7 ^9 S# g- u% r% O" VAnalysis of variance, 方差分析
+ c! e. G: O# m; W: tAngular transformation, 角转换8 [& I( s" U8 P s$ k
ANOVA （analysis of variance）, 方差分析
, m- P# g e; n* B! v* I8 L+ ?5 W, fANOVA Models, 方差分析模型3 |. O: C+ n9 e N! K: i! w
Arcing, 弧/弧旋
! p: |# x6 Q( g6 P) K0 MArcsine transformation, 反正弦变换
" ^8 `6 t3 o( }0 CArea under the curve, 曲线面积
- N: N' f, h) r, `AREG , 评估从一个时间点到下一个时间点回归相关时的误差 . i3 d+ C5 V1 p2 \; {5 c. I; E; D
ARIMA, 季节和非季节性单变量模型的极大似然估计 : ~6 T2 I, Q2 S. `3 W @4 T
Arithmetic grid paper, 算术格纸
# D9 g/ @& ]) V! F1 s# A8 UArithmetic mean, 算术平均数% Z3 p9 |/ `- O+ W/ f5 C/ h; ?
Arrhenius relation, 艾恩尼斯关系8 Q- U% B8 a/ b- m, \! B6 c
Assessing fit, 拟合的评估. G& t8 O1 R: j6 M
Associative laws, 结合律& B% Q& j: f3 r# a2 b# c# w* u. g
Asymmetric distribution, 非对称分布5 m/ a( [8 R6 c0 b
Asymptotic bias, 渐近偏倚
3 q4 w+ X; Z; a" [ g; dAsymptotic efficiency, 渐近效率% o% _+ `" S" D- d
Asymptotic variance, 渐近方差
; v; A) f [" ]6 BAttributable risk, 归因危险度! @& f8 B+ g' U [$ O3 j
Attribute data, 属性资料# y; O/ ?# |8 }6 a
Attribution, 属性6 W. h+ _+ z: @( E
Autocorrelation, 自相关
/ m* x& s$ t& z/ l1 F' I; s$ uAutocorrelation of residuals, 残差的自相关
, i! F. h" |6 {$ qAverage, 平均数" i( n; ~2 c1 u7 d0 E* X) i$ ^0 ] Y
Average confidence interval length, 平均置信区间长度
% Y X9 z- T, l @5 @1 T6 `! UAverage growth rate, 平均增长率
/ [) X# ^( D9 A* XBar chart, 条形图0 v! {9 v5 x& R( a0 `
Bar graph, 条形图
+ o. @4 x6 T z j0 R- lBase period, 基期
9 M; j! b1 Q5 n" L2 h5 a/ K; PBayes' theorem , Bayes定理
/ Z3 R$ |" a6 T- v7 o) eBell-shaped curve, 钟形曲线
+ \& V: }# v. W3 y) oBernoulli distribution, 伯努力分布5 t0 V# X- B8 Y1 }' L$ _( X; @) _
Best-trim estimator, 最好切尾估计量; i C' `+ A% \2 K3 B" L
Bias, 偏性
, H) v, F P0 }) x' g- \Binary logistic regression, 二元逻辑斯蒂回归
2 |; P# w6 C: c& v; ?& bBinomial distribution, 二项分布
9 E# A1 w! U! cBisquare, 双平方8 d" h0 _ O* E7 M
Bivariate Correlate, 二变量相关
% E F6 {9 E/ Y% eBivariate normal distribution, 双变量正态分布
9 ~1 l8 g$ g h3 `. x4 x& SBivariate normal population, 双变量正态总体
# A/ v4 ^: } }7 ABiweight interval, 双权区间
# A: K' k: g; @Biweight M-estimator, 双权M估计量7 ` c6 ^3 L) |1 \, p
Block, 区组/配伍组3 t( Y G3 D; S9 ^: ?) V/ D
BMDP(Biomedical computer programs), BMDP统计软件包, c; ^% c4 o. x+ Y/ v- }
Boxplots, 箱线图/箱尾图
% {, y) T, \" jBreakdown bound, 崩溃界/崩溃点- A# u1 ^. J+ D* @
Canonical correlation, 典型相关; m- C: ~" M; V4 l$ L
Caption, 纵标目0 M3 W; d" c7 T* K: o( p
Case-control study, 病例对照研究
, i9 P2 C/ _+ BCategorical variable, 分类变量
6 X9 d8 { [, z% j" K! w4 [2 C E9 e8 a3 RCatenary, 悬链线
% n. t8 o2 S0 e$ s+ i" {; G$ e# V! R1 qCauchy distribution, 柯西分布
2 X( A S0 I7 m1 q7 W* K* xCause-and-effect relationship, 因果关系: D1 e7 t9 P' K4 v
Cell, 单元# i7 h8 m7 _$ X! ?4 G- s
Censoring, 终检) x8 V/ E; F& v2 e
Center of symmetry, 对称中心. x2 M$ _9 t @' Q0 v
Centering and scaling, 中心化和定标
6 i' p3 _" j; s" ?" v8 qCentral tendency, 集中趋势
4 X1 n A) k% E. `8 P2 VCentral value, 中心值
' r8 p7 j' s" H3 ^9 L4 FCHAID -χ2 Automatic Interaction Detector, 卡方自动交互检测$ E* e0 ~( c) O# ~- J$ Q0 @
Chance, 机遇 j+ J6 X5 D5 x! b" t/ v
Chance error, 随机误差9 l. `* Z/ s1 G. V3 q9 N
Chance variable, 随机变量
: K. w) o$ B% W% K8 O0 G. kCharacteristic equation, 特征方程
/ E& r; s8 C' k8 |; [" s1 B: b) X' ?Characteristic root, 特征根& b6 e2 _7 ^7 r$ Z
Characteristic vector, 特征向量
% D1 O# P8 t e, ~% Z# ~Chebshev criterion of fit, 拟合的切比雪夫准则2 D8 Q6 p, R5 \& ]. I4 @* p
Chernoff faces, 切尔诺夫脸谱图2 S* j, l8 i. E) G3 a. U$ C
Chi-square test, 卡方检验/χ2检验5 w5 f: A9 p F8 h7 q& i
Choleskey decomposition, 乔洛斯基分解
2 L' P% C! N1 J+ L. _! rCircle chart, 圆图
! d$ K: I6 `8 s2 i- @Class interval, 组距
5 S' W/ x3 c% c! ]Class mid-value, 组中值
* i7 r% K" q+ F0 JClass upper limit, 组上限
- q. w& q. Q( f9 iClassified variable, 分类变量- q3 v2 v( f4 H# F
Cluster analysis, 聚类分析
4 @$ f, ^% y- t3 W9 {! w1 K- lCluster sampling, 整群抽样
' g" w0 x0 B$ |- S7 L5 h/ y5 ?Code, 代码
5 V$ a: D/ t1 _! W. c9 J6 \. QCoded data, 编码数据
6 d: P1 U% m$ z& ^; ~- P; b+ VCoding, 编码3 a* ?5 p( E6 J
Coefficient of contingency, 列联系数+ J; S0 q* O/ E! I1 Z! U4 ^5 j
Coefficient of determination, 决定系数
; ?2 a2 \& Q( C( V0 ZCoefficient of multiple correlation, 多重相关系数
6 a- k9 ]+ `, j4 e2 I# NCoefficient of partial correlation, 偏相关系数% d, w3 t( u% Y9 z! x* e1 z3 N
Coefficient of production-moment correlation, 积差相关系数
5 @ s9 H) d# H6 E9 J/ x9 e4 |Coefficient of rank correlation, 等级相关系数/ \' c* n- U. o7 ~& G
Coefficient of regression, 回归系数2 t' }; S" Q! V
Coefficient of skewness, 偏度系数
& ~2 u$ g/ w& D$ `Coefficient of variation, 变异系数 v8 b, s. p8 q
Cohort study, 队列研究7 }; _2 M' p% p
Column, 列
2 ~- b& |! D# S0 V& X7 GColumn effect, 列效应6 e# C0 e$ m% e" s* X0 X5 P# q
Column factor, 列因素% S: s. W1 d0 I3 F/ z
Combination pool, 合并
+ K6 ]! F2 C/ |9 F _+ wCombinative table, 组合表! @# c( r0 u4 x
Common factor, 共性因子/ F6 v/ S& I( p7 b$ O' i! v
Common regression coefficient, 公共回归系数
) p7 h% D9 h. z& j1 a7 kCommon value, 共同值
0 i2 s0 B |/ _2 rCommon variance, 公共方差
) ~& [' W, k$ }% I" XCommon variation, 公共变异
. v9 K6 x D! T* P! mCommunality variance, 共性方差
5 O% ?" c/ ]" v% S3 r, oComparability, 可比性
& Z' v2 M+ c0 R+ U5 @ NComparison of bathes, 批比较
$ V {$ {1 |% e0 T- `# V; T8 MComparison value, 比较值9 h8 b- ]. t/ I0 J
Compartment model, 分部模型3 |! e$ k% M. k$ |6 a) g
Compassion, 伸缩8 N# u( \/ E! Z% S
Complement of an event, 补事件
& J; L1 S& {8 h- S( \Complete association, 完全正相关
( t7 ~1 {8 p9 j1 I/ S8 Z( jComplete dissociation, 完全不相关
) Z2 K% X) h$ |2 f; ]: k: tComplete statistics, 完备统计量& J( E! V4 S1 }; }4 G
Completely randomized design, 完全随机化设计
7 @/ d+ _7 \- ^+ X x9 [5 j( LComposite event, 联合事件8 \( \6 E- R- t7 I
Composite events, 复合事件
% j8 z4 l+ G) e1 nConcavity, 凹性
: x* b K& b+ n8 U8 \Conditional expectation, 条件期望
, B2 G. w$ [( h! m$ D: FConditional likelihood, 条件似然2 S6 ]8 U: A3 A0 F3 ^( P
Conditional probability, 条件概率* }: B# |0 o. l" S( o& L
Conditionally linear, 依条件线性 B1 C% @6 O8 w) V A; h3 c, s) N
Confidence interval, 置信区间) p" y8 ]* j) Q2 I( v8 k' O. U
Confidence limit, 置信限
4 b. A" |5 e M2 D, F: AConfidence lower limit, 置信下限- _# G. D) T J
Confidence upper limit, 置信上限* o3 h% ~0 O( |& p! e
Confirmatory Factor Analysis , 验证性因子分析/ V! D, H7 F# Z8 {7 Y
Confirmatory research, 证实性实验研究! @* r/ B4 `; ^8 O/ K7 u
Confounding factor, 混杂因素+ O& ^$ X2 }% J) r7 s8 z3 M
Conjoint, 联合分析) C9 q8 a% f7 Y$ Y
Consistency, 相合性
' o2 [+ \% Y, M: hConsistency check, 一致性检验, ?) C. c* c1 k0 F0 B
Consistent asymptotically normal estimate, 相合渐近正态估计
, ]3 w( T u6 w; oConsistent estimate, 相合估计
0 `7 \& G6 n s2 J3 LConstrained nonlinear regression, 受约束非线性回归: \9 A3 v$ z$ H( l+ _3 F0 g
Constraint, 约束
4 l% |! W5 n+ O, c4 f) s! U, k& bContaminated distribution, 污染分布! o" Y: I/ a: Z2 B
Contaminated Gausssian, 污染高斯分布
. g+ L' X% Q; v# m3 b/ HContaminated normal distribution, 污染正态分布# d5 L5 g0 v& J
Contamination, 污染
5 n4 k" k; S# q3 t2 j. J! `Contamination model, 污染模型, O+ d3 F! Q0 @% ~- v4 b
Contingency table, 列联表
! T5 K6 _, \3 _" O, ~( E9 sContour, 边界线 n$ n+ |' A3 P* G1 C5 Y
Contribution rate, 贡献率
: C$ X" U' i* j( e) l8 h$ ^/ hControl, 对照; o$ z; q4 l+ k
Controlled experiments, 对照实验
+ H' }. M5 O) X0 qConventional depth, 常规深度5 N# I- G3 \% }; @0 g X6 G
Convolution, 卷积
$ s z4 c, P. H3 ~" y, TCorrected factor, 校正因子* M, c P% R$ n, D) T6 C$ o5 O! n" N- H
Corrected mean, 校正均值8 R0 L, O: c. i7 b4 H2 L# i
Correction coefficient, 校正系数8 q$ P0 X9 ]9 h0 c8 C' Z( U1 h8 u2 L
Correctness, 正确性 Y! x& S$ F& U! `
Correlation coefficient, 相关系数
$ K; v0 T/ s& O# gCorrelation index, 相关指数5 v3 P% d9 B! w
Correspondence, 对应2 A2 _8 ^* r$ k- x0 \4 A
Counting, 计数
6 c! A% B) O# R+ p8 K2 LCounts, 计数/频数
: Y ~2 m0 {3 ^* {4 p- y1 g3 HCovariance, 协方差. ~+ F2 V7 o+ [( c, s# j
Covariant, 共变
0 N+ u% h7 I4 T( _7 RCox Regression, Cox回归
7 B) F$ y: g- gCriteria for fitting, 拟合准则; R( x9 l* Z9 T6 t& P& T _' n
Criteria of least squares, 最小二乘准则" _6 L! p3 D7 M. H, b, m* i
Critical ratio, 临界比
' ]% I" r% D% i/ G2 }9 l" N' K7 ^Critical region, 拒绝域) o. s) M* i) e, f2 M% V+ C0 |
Critical value, 临界值9 u1 Z2 B, ]4 S) g b+ x
Cross-over design, 交叉设计3 e, E9 S: m$ w2 d1 d4 P5 K3 H3 M+ |
Cross-section analysis, 横断面分析7 d8 I% `- c: ~
Cross-section survey, 横断面调查
; S* ~, j( M/ [+ Z. j$ l* z; uCrosstabs , 交叉表
5 S8 l; }- x# L( k) i5 l* f: v4 ~9 TCross-tabulation table, 复合表" S6 \) F# R) K2 G" Y
Cube root, 立方根. g/ S- {' E, t# `1 T
Cumulative distribution function, 分布函数
3 n# L5 y- r( rCumulative probability, 累计概率2 r( {# V. ^2 W% c. m; Q. m8 R9 W0 ?
Curvature, 曲率/弯曲2 ^! ]- q6 ^* @% l$ w
Curvature, 曲率
- F% g7 n7 F% |3 ]* c& \Curve fit , 曲线拟和
+ `4 f# s: J2 c+ JCurve fitting, 曲线拟合
+ L+ m2 j) S- D/ m4 |Curvilinear regression, 曲线回归
( M% j! c9 N% YCurvilinear relation, 曲线关系6 G' y! T: m' a; Q
Cut-and-try method, 尝试法
- m! B$ k5 Z1 g( b h8 SCycle, 周期
6 X% d7 E/ X5 H% y5 \Cyclist, 周期性3 Y6 h) ~* `/ y# W
D test, D检验
8 w1 H6 p1 |/ LData acquisition, 资料收集/ f( T4 M9 {' i0 ?! V4 T$ D3 J& w
Data bank, 数据库* o8 m* |: p- M2 v7 a
Data capacity, 数据容量1 h& d* B* q# @. E6 P3 ~
Data deficiencies, 数据缺乏
9 O3 p( r3 _# y" ]0 FData handling, 数据处理
2 C' Y" i' Z, E) i0 t& mData manipulation, 数据处理$ [8 A( Z( k& `) H
Data processing, 数据处理3 |" l6 K# n3 l p8 @
Data reduction, 数据缩减
: j+ l3 g9 R) R" XData set, 数据集! K& c, z$ y, Q, m1 f, P
Data sources, 数据来源, T# D! M5 b$ h: e5 O0 a
Data transformation, 数据变换. |5 ^ H; X" h6 }
Data validity, 数据有效性7 C4 f( z+ m$ O# @' y6 c# {7 g
Data-in, 数据输入; c8 Z$ {: t6 M& j; t
Data-out, 数据输出
! \- G$ J* b9 K" G& H {Dead time, 停滞期
& k. H, C5 Y( \% N! ODegree of freedom, 自由度
8 i1 o& o4 O+ i# zDegree of precision, 精密度 g2 q3 p" M7 e& ?# L) J& f3 v
Degree of reliability, 可靠性程度* ^& q# Q* E; D1 b1 z
Degression, 递减* }2 @) [2 I! ?$ e
Density function, 密度函数
) y* U2 f, o8 CDensity of data points, 数据点的密度0 M% P- G2 q& l- h
Dependent variable, 应变量/依变量/因变量0 k$ V- a# k* }1 t3 P$ w I+ p
Dependent variable, 因变量
8 [0 {" z7 F3 ?" D6 ?Depth, 深度
' {' T* I5 k6 O7 TDerivative matrix, 导数矩阵0 b% V( l/ d1 K/ e5 }+ b
Derivative-free methods, 无导数方法4 J: L, u( [. J- i; i; S5 _& m/ G
Design, 设计- o& ~# `) B( X; |1 x
Determinacy, 确定性+ }5 X9 |1 t1 Z; C
Determinant, 行列式
( u4 K! H8 O3 k. P/ I& W1 yDeterminant, 决定因素
$ Q3 c1 E1 ^, T* eDeviation, 离差 T+ m x, F/ b W5 D* W
Deviation from average, 离均差
/ E' N* f% ?4 ?% Q7 N9 d6 uDiagnostic plot, 诊断图
) J3 @- [; [$ h- BDichotomous variable, 二分变量
( h+ F) Y3 ]: t z. D! f. nDifferential equation, 微分方程# i/ _/ J) u9 N w t% c Y4 B
Direct standardization, 直接标准化法
K- c+ z* X$ z" b$ `# pDiscrete variable, 离散型变量
2 Y3 N c2 t/ |6 q0 m/ `* |DISCRIMINANT, 判断
/ W5 o8 w3 d3 W$ tDiscriminant analysis, 判别分析: L% D# A: C. N0 L p) t
Discriminant coefficient, 判别系数7 e f7 r& T' G1 `
Discriminant function, 判别值( \2 ~: S6 G+ u: d' Y* N2 ]
Dispersion, 散布/分散度" D9 h( `5 P4 c0 A
Disproportional, 不成比例的( L8 m3 x5 Y$ g+ r
Disproportionate sub-class numbers, 不成比例次级组含量
1 g+ H5 F* p) H8 U* S/ hDistribution free, 分布无关性/免分布
# Y) R, h* |9 h4 h) s( h5 j3 u" f, XDistribution shape, 分布形状9 n3 W3 u" p2 j, J
Distribution-free method, 任意分布法
3 g2 R, Y9 `3 e" L& C5 l# Q+ S; EDistributive laws, 分配律
7 ]: K' n2 Z% _: W9 w* c3 qDisturbance, 随机扰动项
4 A* e, i; A6 A; _; ~Dose response curve, 剂量反应曲线6 O( j4 d5 w" O7 d
Double blind method, 双盲法
3 u% X# t: Y4 H% b: JDouble blind trial, 双盲试验: H7 w3 F' ]) C2 K
Double exponential distribution, 双指数分布
x$ j3 Y$ q; T! {& t' C1 fDouble logarithmic, 双对数9 A. x4 n& X0 N: v! ^
Downward rank, 降秩( q R. r/ k6 p3 p. k9 J
Dual-space plot, 对偶空间图6 w/ p. z* I5 _
DUD, 无导数方法
0 S4 x# _* @1 v0 T, i lDuncan's new multiple range method, 新复极差法/Duncan新法! e4 K4 b# ]4 H
Effect, 实验效应
# _9 C; c6 v0 I& v% _ _Eigenvalue, 特征值9 D6 s7 f/ d+ d" z& C8 m
Eigenvector, 特征向量
1 b2 S1 g! r4 M, W! _( SEllipse, 椭圆 G( O( A+ `0 q! a% P4 P
Empirical distribution, 经验分布
! b5 ]/ c9 [" j! OEmpirical probability, 经验概率单位
" A4 k4 D" g; VEnumeration data, 计数资料8 C' N9 G: c* D: o4 h
Equal sun-class number, 相等次级组含量
7 a" H( H, z8 [4 ?, y8 |" `Equally likely, 等可能3 F& k& }% E) _3 f' m
Equivariance, 同变性6 f3 L* z' d* y- K
Error, 误差/错误
1 a4 Y4 {; Y. B4 Q, yError of estimate, 估计误差
- j, v3 }) W/ W8 z, IError type I, 第一类错误- ]% Q9 T/ w( ]" |" m
Error type II, 第二类错误6 @0 b/ D6 Q( c' r, v% `
Estimand, 被估量* ^1 |8 i: X" ?# G
Estimated error mean squares, 估计误差均方
1 S$ x, g6 W# S( Q, ^% H" K$ WEstimated error sum of squares, 估计误差平方和
" F' b+ l. b# u' t( x# l6 C% QEuclidean distance, 欧式距离
! A- o/ _# `2 r6 J& _& I3 }+ l n' FEvent, 事件
9 w, Z6 F% g6 G: W7 J3 H# ]0 P3 HEvent, 事件
+ R& m4 u' O7 R1 K+ M6 _Exceptional data point, 异常数据点9 C a* J2 t- g' D
Expectation plane, 期望平面3 c( X: |* C2 i5 j7 W
Expectation surface, 期望曲面
! J$ O" g0 V- P- N @. c3 FExpected values, 期望值
- h6 z/ J, R8 D' g/ F: q1 c) SExperiment, 实验
0 T: G0 n5 }, KExperimental sampling, 试验抽样 v3 F6 |7 A( u) U$ |- N
Experimental unit, 试验单位
2 r5 r$ d2 v. g( h1 L! Z! ^Explanatory variable, 说明变量
* }4 r9 k' d- M& G3 q' e* sExploratory data analysis, 探索性数据分析
7 n {" }; v7 Q7 q! _( q+ WExplore Summarize, 探索-摘要% F- }3 {& S" h: k7 r& S. k
Exponential curve, 指数曲线0 h) X6 G! C" @+ w, u. p- X
Exponential growth, 指数式增长
/ K5 ^: f: ]0 E% Z- cEXSMOOTH, 指数平滑方法
! M" v# i- x' S4 D. ] D6 BExtended fit, 扩充拟合, [4 b ^) S+ @
Extra parameter, 附加参数" \$ n2 V2 |0 j+ ^ r" P0 T
Extrapolation, 外推法
|5 m4 t( c1 X2 E4 Z& a% yExtreme observation, 末端观测值/ P+ ?' r3 s. y: `$ l! H
Extremes, 极端值/极值1 l4 s+ ]' R, t; w9 o
F distribution, F分布
2 u6 w: R5 I4 GF test, F检验( m# w" O; K' C) C7 c5 R0 {, n' ^$ S$ g
Factor, 因素/因子
8 e$ B; A& w0 Q9 ?' ^0 LFactor analysis, 因子分析" p3 v+ |) @' G3 t
Factor Analysis, 因子分析$ D8 l! x% ^8 ]7 n
Factor score, 因子得分
, V( P, M$ {8 n5 eFactorial, 阶乘' Q8 w' y( s+ Y. n7 x& g
Factorial design, 析因试验设计
- S/ g& t0 n8 T: [8 IFalse negative, 假阴性
6 t* y5 \+ R9 u- l, V9 O% [False negative error, 假阴性错误; |# L( _6 y a* q3 [+ W
Family of distributions, 分布族
8 E7 P( w4 L1 yFamily of estimators, 估计量族
% X' q1 K9 ^: n7 E8 }4 AFanning, 扇面$ D. @* ]0 I# C; {
Fatality rate, 病死率0 w! J ~: D! G
Field investigation, 现场调查
* B4 C9 [* L4 n3 J& X! \Field survey, 现场调查; n. {* @3 E9 K/ s& h
Finite population, 有限总体
$ F4 o( F' ~, `8 nFinite-sample, 有限样本
9 U8 I8 V+ ~, l& y/ R% `, g; lFirst derivative, 一阶导数
W8 E& r+ N, }* R% e& E/ n3 P* YFirst principal component, 第一主成分- g& _: }2 W9 {# U+ |' f1 N
First quartile, 第一四分位数
, _& Z! [; x& v7 S, xFisher information, 费雪信息量
: o9 v6 g/ V( T3 E @+ YFitted value, 拟合值
9 ^$ ~" Q W1 {) Y8 a! f/ O* jFitting a curve, 曲线拟合
, m! S7 h, g& u' C) C+ G6 iFixed base, 定基
, a* B! `* e% J0 l; w0 yFluctuation, 随机起伏
+ ]9 ~; m% \ i+ x4 \. E# fForecast, 预测
8 ]; H! Y/ Y4 N2 p( P! f" SFour fold table, 四格表
+ f$ V6 t- W% _ w- O: {1 ]Fourth, 四分点% c2 N9 t2 g2 \4 O. [( H/ l
Fraction blow, 左侧比率' p0 `. \2 d. d# c
Fractional error, 相对误差0 f- @- O! S2 V: J. t) u- k
Frequency, 频率. }6 D4 P `4 Q2 }' G
Frequency polygon, 频数多边图
9 H6 U: F& V4 n6 X) mFrontier point, 界限点3 ]3 k* U$ v0 x7 q: W U
Function relationship, 泛函关系
; j1 j8 g9 P/ j2 BGamma distribution, 伽玛分布 ?0 m2 a- ^: \, |5 `7 x) k
Gauss increment, 高斯增量
* z, l4 O3 W/ _3 d( D& r8 { ^Gaussian distribution, 高斯分布/正态分布
% [$ G4 Q2 r: a2 ~Gauss-Newton increment, 高斯-牛顿增量
/ Z; X8 |: E7 j% A! s( v/ JGeneral census, 全面普查
9 k# z; i. e7 v' N* wGENLOG (Generalized liner models), 广义线性模型
! |3 k$ [7 Y$ {- xGeometric mean, 几何平均数. E2 C: Z; o5 |$ i% [: c% S/ A
Gini's mean difference, 基尼均差: Z" b- S0 Y/ T. q$ E
GLM (General liner models), 一般线性模型 ( j9 E7 V O# x! s- ?( O
Goodness of fit, 拟和优度/配合度0 Y4 A6 H( J, r& f( b3 K
Gradient of determinant, 行列式的梯度/ u5 w* H0 Y# Y7 [
Graeco-Latin square, 希腊拉丁方
6 G6 T. K+ K( N% s5 S3 h% m" N' UGrand mean, 总均值. ]# w1 x# w- a2 v, _
Gross errors, 重大错误, k' P( L7 Y3 s* ~6 H4 g9 k
Gross-error sensitivity, 大错敏感度
K U: R, U3 ]$ J3 z9 j. c4 JGroup averages, 分组平均
2 ~. O( p$ }' m0 E H) `Grouped data, 分组资料5 M+ U2 i: P; e7 B) M3 [
Guessed mean, 假定平均数
2 c+ F7 z: t" E! z9 [$ ^/ n2 W$ ZHalf-life, 半衰期
/ Y" c7 O L4 Y" C0 n/ jHampel M-estimators, 汉佩尔M估计量
5 D: s! ?1 l; J8 r0 k8 A% m vHappenstance, 偶然事件8 U( \" Y1 D/ Q5 C. d& B; ?4 j
Harmonic mean, 调和均数" k$ o6 Q8 x3 ~* c2 H
Hazard function, 风险均数
/ O1 l3 \; x- q3 _# sHazard rate, 风险率 Y7 \0 f! Z9 a8 O
Heading, 标目
9 t; v5 W3 E. e6 W. @& G; ~Heavy-tailed distribution, 重尾分布
1 U2 p1 v0 q* S! m5 G% tHessian array, 海森立体阵
! R: A% {. \0 H( LHeterogeneity, 不同质
% A9 Q1 }) B$ F5 ?- j' g. ]. S- fHeterogeneity of variance, 方差不齐
3 x$ e& D& l0 x4 s! PHierarchical classification, 组内分组" _$ G. q2 v) m8 {
Hierarchical clustering method, 系统聚类法
) j2 | L& ~7 Y7 }0 gHigh-leverage point, 高杠杆率点8 w6 s, I. A* B5 o2 v+ E
HILOGLINEAR, 多维列联表的层次对数线性模型( z7 m3 o+ R3 E; ]# c
Hinge, 折叶点
2 F1 |, B0 v8 G% A7 a o- HHistogram, 直方图6 \) W# Z/ a0 V9 a) E/ x$ N. i& P
Historical cohort study, 历史性队列研究 5 Z, _+ v# |0 u7 x
Holes, 空洞
, l9 k) Z- K5 x" T! sHOMALS, 多重响应分析6 D! b6 ~4 i2 @% F& r/ X
Homogeneity of variance, 方差齐性) Q/ F4 I& b: x) n1 x
Homogeneity test, 齐性检验# |+ x+ G9 v; B/ v4 R8 f
Huber M-estimators, 休伯M估计量$ E% Z9 E8 C* {. F+ X* U
Hyperbola, 双曲线. X4 `: j3 x5 w* W; r
Hypothesis testing, 假设检验* A' v; e) q; ^/ a
Hypothetical universe, 假设总体
3 @- a7 z6 x$ F" Z4 J6 ?Impossible event, 不可能事件
7 n5 e/ z1 y2 a( L. GIndependence, 独立性: i9 N8 ^: L. W% G4 K- l
Independent variable, 自变量
, |& \$ S0 u, [Index, 指标/指数" {' Z, n. r$ e' j) D
Indirect standardization, 间接标准化法
, ^& g4 o4 E+ C8 S) F- t4 S# Y$ dIndividual, 个体& n6 D4 F8 t4 z8 Q- O
Inference band, 推断带
4 t6 I2 \' q4 p' I% [2 A4 d# V Y1 u1 ?Infinite population, 无限总体
" |% w3 B$ y0 V( C9 S) h5 vInfinitely great, 无穷大$ z0 x" ?$ e2 q8 S9 ? A8 @1 L
Infinitely small, 无穷小
) `- j1 ]# B1 ~8 l& zInfluence curve, 影响曲线
! @' i, n( l. o2 C8 G/ lInformation capacity, 信息容量* E8 Z8 _; Z% |5 Q4 \
Initial condition, 初始条件8 b! F- O. H( g7 w; E
Initial estimate, 初始估计值- {3 \7 j/ l, g8 c9 R8 @
Initial level, 最初水平( d! z- D& a( Y( b! y. [& V* Y
Interaction, 交互作用
( {2 j) R; }* V; t9 |Interaction terms, 交互作用项
6 t1 r4 W8 J+ _' @Intercept, 截距
3 R4 v# ?- R$ e9 S w0 k0 c' G$ K# jInterpolation, 内插法: Q" X. G) @9 e; R' }* p8 C
Interquartile range, 四分位距. Q1 C Y2 I, X! \0 w
Interval estimation, 区间估计; d% l; e x `& Q4 b
Intervals of equal probability, 等概率区间
3 o, d3 t5 t# d P8 L. F, ZIntrinsic curvature, 固有曲率
, |( Y) w) Z6 C+ H+ l5 R& N, ZInvariance, 不变性
6 X j9 J! `) _# f; EInverse matrix, 逆矩阵$ Y8 t5 R; i: j3 l9 ^5 Y$ B
Inverse probability, 逆概率" H/ L6 y, V Z" z+ l
Inverse sine transformation, 反正弦变换
* |3 e3 ?- H2 H% x2 N4 u9 C5 x/ fIteration, 迭代
* |, U4 M1 |* w9 @6 T7 ~Jacobian determinant, 雅可比行列式
3 O- X$ N2 @0 u( @( wJoint distribution function, 分布函数
. E+ j# D$ v) k0 Z8 r9 C6 b6 ^Joint probability, 联合概率8 o5 X/ m. q! b2 Z
Joint probability distribution, 联合概率分布3 y" S4 M0 v. L6 a6 u1 c$ o
K means method, 逐步聚类法9 G1 P) O# A7 H# H: D) h7 }
Kaplan-Meier, 评估事件的时间长度
7 t2 a) T6 z5 G0 QKaplan-Merier chart, Kaplan-Merier图" a) {) D+ T3 N$ _- S! U
Kendall's rank correlation, Kendall等级相关9 z/ e' p- q2 I/ d8 B! W. U
Kinetic, 动力学9 }: `0 {* H& \! I! O- I; b' ?
Kolmogorov-Smirnove test, 柯尔莫哥洛夫-斯米尔诺夫检验
7 X' {* f8 T; TKruskal and Wallis test, Kruskal及Wallis检验/多样本的秩和检验/H检验' i; Q9 _6 ~7 Q4 Z
Kurtosis, 峰度2 W% }: y. V3 ?% N- g9 L. b+ R
Lack of fit, 失拟: B9 y3 G) Q2 V4 m$ i+ d
Ladder of powers, 幂阶梯
% c; i* ?9 R1 [2 U: LLag, 滞后
* _: F; u7 M* Z( [ o. w: B0 w! t: FLarge sample, 大样本
5 |$ g6 ~; M( g _# sLarge sample test, 大样本检验1 ~' ]1 d* L( B' J; P
Latin square, 拉丁方
# I3 b7 }4 w, r. R8 M/ WLatin square design, 拉丁方设计
K9 t& a$ s7 y1 e) k' u7 _Leakage, 泄漏3 J3 x+ {, @. c! C( ]5 `3 B" M, r
Least favorable configuration, 最不利构形
8 U- p9 `0 x) v# l6 m; V5 ALeast favorable distribution, 最不利分布; z& z1 Y- @3 @6 Y( p/ f/ W2 [
Least significant difference, 最小显著差法: a! X. a* ?. {& w7 M* c
Least square method, 最小二乘法8 G$ U5 @. v, T: i. s9 S
Least-absolute-residuals estimates, 最小绝对残差估计
3 e0 B- T6 z0 W0 ELeast-absolute-residuals fit, 最小绝对残差拟合2 s% Z# M% F1 S& I, D0 U
Least-absolute-residuals line, 最小绝对残差线/ D; ~2 O( K( K0 r
Legend, 图例
% R: a: r1 W% J8 b/ OL-estimator, L估计量4 C/ R) }6 A0 Z& |8 @8 J' B4 Q
L-estimator of location, 位置L估计量
+ N6 O4 r* E# V& j3 S& g ~L-estimator of scale, 尺度L估计量
2 b7 ~" h1 K: P. o2 a# g7 T7 iLevel, 水平1 J: }$ C* I$ r1 n& H' B; c
Life expectance, 预期期望寿命! a7 [6 {* i: U
Life table, 寿命表$ f" s! H- L! _/ d
Life table method, 生命表法
# P* p2 [5 L0 B! ULight-tailed distribution, 轻尾分布
% P/ v1 c% }7 Y& k5 [/ [Likelihood function, 似然函数
" D. b x. w9 pLikelihood ratio, 似然比( z; R$ K: d3 ^8 @
line graph, 线图& w# \. F j- ?5 b2 |# e+ `
Linear correlation, 直线相关' L4 [4 h0 v/ g0 [7 F
Linear equation, 线性方程: L- K3 {' i, g. D# _9 _
Linear programming, 线性规划0 o+ G: l! l# i+ `
Linear regression, 直线回归* o& J0 }) I8 c& F7 G! q* ^2 G' O% O
Linear Regression, 线性回归
. Q* n, h0 p* D8 z! wLinear trend, 线性趋势6 @; O2 j& d: \+ d' f
Loading, 载荷
8 E2 Q, |9 c7 XLocation and scale equivariance, 位置尺度同变性
3 L2 H8 w0 ^$ W7 |7 i8 q% ZLocation equivariance, 位置同变性" h; V3 H/ i5 q
Location invariance, 位置不变性
) `) @$ T: G, |1 A/ V+ nLocation scale family, 位置尺度族- M- j, l& S7 H n. b: Q
Log rank test, 时序检验 ! h3 \, \ `# \- ^6 C
Logarithmic curve, 对数曲线
- }. }- j6 o. Z5 W9 TLogarithmic normal distribution, 对数正态分布# D; j5 C% B- ^! }1 j
Logarithmic scale, 对数尺度1 F, s& `, e5 b4 g8 M
Logarithmic transformation, 对数变换$ f+ H' r t8 t# K/ j$ k) b
Logic check, 逻辑检查
6 z) E1 ~8 \. ^8 O3 a9 J6 @2 |Logistic distribution, 逻辑斯特分布/ t; H: k% s2 Y( d
Logit transformation, Logit转换% K3 L2 Y: p& Q, ^( f$ m
LOGLINEAR, 多维列联表通用模型 7 \# e0 R5 z% [9 W( P$ A
Lognormal distribution, 对数正态分布
1 f4 ~9 ^4 f( uLost function, 损失函数
$ H7 @7 q7 `/ BLow correlation, 低度相关3 w2 w# R I1 O; w" F, I
Lower limit, 下限; g5 b0 s5 c6 v
Lowest-attained variance, 最小可达方差
/ ?/ G# W7 y# zLSD, 最小显著差法的简称
& b- [# D5 n7 Y+ l2 Q6 `/ I+ NLurking variable, 潜在变量# `$ d B" |7 A. D# J) B& u, Q
Main effect, 主效应9 w: h, w/ [7 Z* N
Major heading, 主辞标目3 Q5 R' f- K4 Z3 f, }
Marginal density function, 边缘密度函数* h; }* Y) k: P* [3 }
Marginal probability, 边缘概率
/ r' }; Q: \, U6 c* ?4 \5 tMarginal probability distribution, 边缘概率分布
3 w5 p. j4 S# ~Matched data, 配对资料) _8 T/ _2 ^# d9 b8 R9 P, ]. w' Z
Matched distribution, 匹配过分布1 V9 B) k! m& e2 g: _. f
Matching of distribution, 分布的匹配
: N0 F+ r4 H: ?( J0 a4 s: jMatching of transformation, 变换的匹配
. O. X( Y8 k7 O! WMathematical expectation, 数学期望" b; p: @& V3 |( G5 n
Mathematical model, 数学模型
, H: h0 y! `+ N1 B" Q+ r& yMaximum L-estimator, 极大极小L 估计量7 |1 U, b) |- o5 [: x
Maximum likelihood method, 最大似然法
/ J1 V( i8 A3 @& G9 {Mean, 均数
* X. S: ]! p) U8 L+ \Mean squares between groups, 组间均方. L7 z; L6 P* b8 d" x0 B+ \
Mean squares within group, 组内均方; w7 W2 x: C: F6 Y0 f) A5 ~$ o
Means (Compare means), 均值-均值比较
; b9 _9 N2 l) U% k/ R) b5 K7 rMedian, 中位数( o6 o+ Y8 C( D1 R3 Q% K5 A
Median effective dose, 半数效量
. N$ D* W' v+ }Median lethal dose, 半数致死量
8 F( q6 T1 o& I+ l9 s" F6 P; rMedian polish, 中位数平滑. T7 C$ W2 F8 N9 ]
Median test, 中位数检验2 y2 V2 l6 C& j# J3 C4 n& O
Minimal sufficient statistic, 最小充分统计量) c$ X R/ K: d+ r2 m! _
Minimum distance estimation, 最小距离估计8 {9 b: P! G4 E U/ M, a! M
Minimum effective dose, 最小有效量$ t/ T2 P, `: W0 j$ A5 X, v
Minimum lethal dose, 最小致死量
# ], ^; T5 v) Y: ~/ oMinimum variance estimator, 最小方差估计量0 c1 @; d3 Z+ L4 t
MINITAB, 统计软件包
' Q- Y) }6 `- }Minor heading, 宾词标目
7 V/ H; m' V3 g/ J# s0 M) G+ f& B' o+ WMissing data, 缺失值 I( }1 `+ i4 c: q' i- }6 U5 W0 P3 n3 }
Model specification, 模型的确定
5 K' b7 r* b8 j5 FModeling Statistics , 模型统计
% M. S" `& Q. F" s2 t" d6 Z. E7 AModels for outliers, 离群值模型) k U0 x" V& T2 F. A
Modifying the model, 模型的修正6 H# l+ K; ?& c5 p
Modulus of continuity, 连续性模
" S7 E+ C- U0 x: hMorbidity, 发病率 % W7 [; s/ M8 Q/ h
Most favorable configuration, 最有利构形
6 Q- D( G4 r3 Q. g1 G9 dMultidimensional Scaling (ASCAL), 多维尺度/多维标度
2 [+ @& n% D H6 SMultinomial Logistic Regression , 多项逻辑斯蒂回归
/ I+ h. T1 N% {- S$ BMultiple comparison, 多重比较 G0 D" I E# N8 S9 m3 L9 o
Multiple correlation , 复相关) w p5 H+ `2 u# i$ ?
Multiple covariance, 多元协方差
4 f( I M4 `, ]Multiple linear regression, 多元线性回归
( Y+ n2 h& O* V+ G% t4 _Multiple response , 多重选项 \/ L% K* s3 H- U: a
Multiple solutions, 多解
) |! B0 |- V' H3 ?4 hMultiplication theorem, 乘法定理$ m9 p5 d2 b" ?$ J" t* l# |
Multiresponse, 多元响应
% l% @& K; p1 O4 F+ q WMulti-stage sampling, 多阶段抽样( o! V. N; ~6 L
Multivariate T distribution, 多元T分布
0 w" k/ ]0 \2 H0 fMutual exclusive, 互不相容* q% y) O- y3 {( `8 w4 f3 O2 N
Mutual independence, 互相独立
9 b0 k x% h2 e! [7 h9 sNatural boundary, 自然边界
* Z' U) }' `/ Z, s0 ?Natural dead, 自然死亡2 X: w! P" t# q {1 _
Natural zero, 自然零( Q4 _& u0 {- a! b) Q; i1 Z
Negative correlation, 负相关
0 X: [* v9 W! P( r U: @Negative linear correlation, 负线性相关
( Q F( [8 K" xNegatively skewed, 负偏" B; d" F& u) `& k
Newman-Keuls method, q检验
+ \5 G( m4 ]/ a, K1 t; Y' t A9 ENK method, q检验
* [" J( g9 H, G" s9 tNo statistical significance, 无统计意义( K# ]! N+ K# X5 K) H2 h3 C
Nominal variable, 名义变量
$ i C' K* l2 Z/ j( TNonconstancy of variability, 变异的非定常性' V9 v# L' D# \, R3 s1 h
Nonlinear regression, 非线性相关% e4 e; [, z S, ~8 |- i
Nonparametric statistics, 非参数统计# X* C. W i+ q; E/ z5 t; S
Nonparametric test, 非参数检验% L1 j0 `6 ?6 u u6 E4 p
Nonparametric tests, 非参数检验& x0 z/ V3 m8 C* Y' y9 J
Normal deviate, 正态离差
2 b- s9 |4 L; ?6 YNormal distribution, 正态分布
! I0 w, ^& K0 R/ P- aNormal equation, 正规方程组
3 O' O, K& ~9 E# B3 aNormal ranges, 正常范围
7 N1 I8 e; v3 c1 o9 q) t) mNormal value, 正常值
e; ^+ }! Y3 @* e8 g1 [: @% [Nuisance parameter, 多余参数/讨厌参数
2 J% f {8 `) k6 {: s. X1 KNull hypothesis, 无效假设
( J' @( k, k w: w( q1 wNumerical variable, 数值变量7 P) P7 N# P! G2 h" W% Y) C' f
Objective function, 目标函数" ?; P" w' b4 C
Observation unit, 观察单位
" d- u+ i& R2 x3 V4 [' Q3 p% jObserved value, 观察值9 T2 o; X( V% i5 R. j& m
One sided test, 单侧检验1 K( C1 e6 Q, w5 E7 g) K2 z/ r
One-way analysis of variance, 单因素方差分析) _( U1 g& ]' f$ o. g
Oneway ANOVA , 单因素方差分析
2 e1 j$ T/ K; f& i( F9 B" COpen sequential trial, 开放型序贯设计8 o' _- Z3 I4 S& y9 ^
Optrim, 优切尾
' {& o6 C% r ] ~( @Optrim efficiency, 优切尾效率# G! Q! F9 h2 o
Order statistics, 顺序统计量" w% g' `& Y4 L1 ^# ?( x- V: H
Ordered categories, 有序分类' N7 D- J1 m8 n+ [" r
Ordinal logistic regression , 序数逻辑斯蒂回归5 L! ]/ {8 c+ l$ T3 I! }
Ordinal variable, 有序变量
! O4 d) s+ C+ F3 j T8 YOrthogonal basis, 正交基! {+ E' T/ Y ~7 m
Orthogonal design, 正交试验设计' L) h" P0 L" w- ^: D3 H2 E
Orthogonality conditions, 正交条件' j0 E1 y9 b4 L/ Z* p
ORTHOPLAN, 正交设计
& P% U' \9 N+ y& UOutlier cutoffs, 离群值截断点/ c/ r; q* g5 p5 _3 y
Outliers, 极端值1 s, e' d$ H- [' A/ j0 @/ L
OVERALS , 多组变量的非线性正规相关
1 h1 s4 {( C+ `! @' c5 `Overshoot, 迭代过度
4 ^/ N2 R% i. J, uPaired design, 配对设计
% g4 l: h0 r. x9 GPaired sample, 配对样本
9 z6 k2 Z+ }5 `, b4 b% _* X! i3 `Pairwise slopes, 成对斜率
) l! Q5 N Z9 B4 _# `& A+ B6 VParabola, 抛物线
G: i5 S0 _8 s* W7 r6 UParallel tests, 平行试验 J" t! [. j' B) w$ ]( Z
Parameter, 参数
9 C% @$ Z( w6 u4 F; mParametric statistics, 参数统计# H! U( v0 C% j8 I
Parametric test, 参数检验
( p6 h |0 B% P# K" v, D, F3 lPartial correlation, 偏相关
9 s6 D, s& }, P, Z0 J6 ?4 qPartial regression, 偏回归' f" \6 @$ o2 h
Partial sorting, 偏排序6 R! C L0 I6 Y2 R0 L2 g
Partials residuals, 偏残差
, X' O& i8 p* D; }Pattern, 模式
0 s" J+ o5 r. j' Z$ e' J5 hPearson curves, 皮尔逊曲线; [6 } I4 N0 J9 B
Peeling, 退层 b+ R4 ^" {1 X2 x! K* }
Percent bar graph, 百分条形图+ G- Y/ m3 |/ s& \& T, w! `
Percentage, 百分比2 t v# O( k0 r* M
Percentile, 百分位数
7 Y* P8 F1 f% KPercentile curves, 百分位曲线
. t! q: D) S# v2 K, _8 ZPeriodicity, 周期性
2 P! T& B* m2 k5 v8 WPermutation, 排列
8 V: C8 [8 ~ FP-estimator, P估计量5 B. a0 x) ]+ @8 L" ]& q
Pie graph, 饼图
. ^. z7 ?& V- S2 `+ s6 FPitman estimator, 皮特曼估计量* N/ p# a3 ^& M0 k! S6 d8 q
Pivot, 枢轴量" ~; F, u: [4 Y6 l/ z% \: g
Planar, 平坦
: `5 p! x$ g1 I% P. N ~Planar assumption, 平面的假设
/ r0 [ R5 r6 [/ B6 S* R. Y: j( kPLANCARDS, 生成试验的计划卡% o* Q7 V8 D2 l6 Z7 U7 i# l w
Point estimation, 点估计; Q2 Q. n3 e+ N$ V5 a- _
Poisson distribution, 泊松分布
0 S2 @+ |: H8 pPolishing, 平滑8 _ v% |, G8 r9 F: P
Polled standard deviation, 合并标准差
7 Q# U, h) V; g. |& X0 iPolled variance, 合并方差' t' D% f5 c: ~& [2 ^
Polygon, 多边图
# i% N" @* U9 C- JPolynomial, 多项式
. @7 |" [, e2 n- Y! Z- A' bPolynomial curve, 多项式曲线8 e9 E. Z# s4 E' I
Population, 总体
+ y$ X, e. V5 j2 o& h9 @Population attributable risk, 人群归因危险度5 k1 g5 J: ^- J0 E4 P1 c- l
Positive correlation, 正相关: a( w! D. H0 s8 P2 S
Positively skewed, 正偏) C2 f, T7 N+ w% X+ O
Posterior distribution, 后验分布
" l/ H6 D5 l% gPower of a test, 检验效能- ~% k( b2 A; D7 U6 i0 a
Precision, 精密度
2 ]1 B) C1 Q& K' ^1 nPredicted value, 预测值
4 e/ N4 `6 h* @7 I, j3 L e; r$ t/ u/ XPreliminary analysis, 预备性分析# ~6 }. |. Z9 n, H7 s7 _
Principal component analysis, 主成分分析: r& F& D1 ~& B' T+ T( {' j' |
Prior distribution, 先验分布
% R6 k, e7 U; `, o6 X ^Prior probability, 先验概率" m5 Q( s5 A' o' h ~! K8 v$ o B: ^
Probabilistic model, 概率模型
; ]. P& B( y# n1 A; Kprobability, 概率
" h" D/ q2 v' @4 p0 \, x: B5 qProbability density, 概率密度
' u. ?% A7 c+ f5 R. y+ |1 U. _Product moment, 乘积矩/协方差
- Z+ Y/ O0 v- ]3 N* ~5 {: j: oProfile trace, 截面迹图
$ U3 {2 j' H f( L- jProportion, 比/构成比
+ C) ]" f+ @2 w+ m5 K+ JProportion allocation in stratified random sampling, 按比例分层随机抽样
5 U0 h5 }3 E9 O' R. ~ H4 lProportionate, 成比例0 F) |* Q) N6 M+ ~2 d" `
Proportionate sub-class numbers, 成比例次级组含量' _% L U+ r0 | x9 l
Prospective study, 前瞻性调查0 |: E% R2 r6 X
Proximities, 亲近性 A% e0 a6 F Q; r) W$ J- _
Pseudo F test, 近似F检验
' g. \( _! W* q, g& w G7 jPseudo model, 近似模型
! A; {* l1 L$ q' r/ S, D5 J) D0 j yPseudosigma, 伪标准差' d" h+ g) ~8 E1 B4 V
Purposive sampling, 有目的抽样
) _! |2 l( l7 N# a5 X2 b3 c. H" CQR decomposition, QR分解
) b8 R. k# g3 z5 v& mQuadratic approximation, 二次近似' ^$ W0 u7 K# P- ~
Qualitative classification, 属性分类
+ b5 p" H& e4 K0 k/ kQualitative method, 定性方法
' d$ o' g, v6 O( k1 n, ~7 AQuantile-quantile plot, 分位数-分位数图/Q-Q图
) ?0 g! i( v& v) O6 mQuantitative analysis, 定量分析
+ F) d/ p" Z1 e! p8 k$ YQuartile, 四分位数
' u `- q) k. W5 j# U% BQuick Cluster, 快速聚类
, z8 e2 ?: G6 G( t( _' hRadix sort, 基数排序 D$ O' |$ }" C q; E% `
Random allocation, 随机化分组
* y* n' Q# d+ o3 ?0 y4 X$ XRandom blocks design, 随机区组设计
. i7 D6 c$ n* R4 Z: ]7 r$ |3 S8 sRandom event, 随机事件! e/ y$ O+ E+ [2 H8 v
Randomization, 随机化
+ \+ F* w Z$ M; eRange, 极差/全距) O" x Z1 s/ z: P7 T9 g% ~6 ]
Rank correlation, 等级相关
& ^% p+ G x! N9 C' L- rRank sum test, 秩和检验
( o5 w: O6 T4 }, _Rank test, 秩检验
3 F. K$ [# z- r; WRanked data, 等级资料# y, Q5 z; b1 D3 N
Rate, 比率7 s# o) ^, r& C- |$ m
Ratio, 比例
6 Q4 _0 M8 |, k, W9 b7 g0 MRaw data, 原始资料
0 L! o0 [; n& o' ]5 J- WRaw residual, 原始残差8 ?: \4 ^$ O3 T( `, \, @ p2 N
Rayleigh's test, 雷氏检验
3 d( W" ^& h8 R5 {- c L9 xRayleigh's Z, 雷氏Z值 - ]' B* T- Q2 \$ ^( k
Reciprocal, 倒数
: }- Z* S6 s6 F; x. [- T/ [( fReciprocal transformation, 倒数变换* C" K1 T+ B1 |; Q+ P3 } Q$ `5 i& e
Recording, 记录
- [; h X/ f5 W- J; D. FRedescending estimators, 回降估计量
, J" L3 m4 b: C6 A% u$ a( J3 pReducing dimensions, 降维' X0 L: _6 D. l ]. p. Y6 m+ u
Re-expression, 重新表达
# \, F! a f! r1 h. ]( Y6 nReference set, 标准组; f0 x* W( F$ J9 m
Region of acceptance, 接受域
1 V" e- L4 ~( f7 x1 x) h8 M6 F$ iRegression coefficient, 回归系数' f4 `( d( ?( t
Regression sum of square, 回归平方和
$ P# \ o1 w( o% b- sRejection point, 拒绝点, K O3 `. F8 q9 A0 V2 G
Relative dispersion, 相对离散度
9 F h. m0 S; ], q6 ]. \Relative number, 相对数
; w# k. k8 ?9 ?' G0 DReliability, 可靠性+ L7 H. j' N) v! c' l* W
Reparametrization, 重新设置参数3 R/ ?$ A- w& c( p# t
Replication, 重复: m2 n. {" k" |7 N) v% A( Y# n
Report Summaries, 报告摘要. A4 v% m, r% L$ ]# H U4 j
Residual sum of square, 剩余平方和
- r$ v7 Q5 U: i4 e3 OResistance, 耐抗性: _5 ^7 J" Y* S# z
Resistant line, 耐抗线
5 W* b$ {; w% R: g- J* `; {+ W# ?Resistant technique, 耐抗技术
6 z4 U( Y/ ~* i# R/ iR-estimator of location, 位置R估计量 U! V: `9 X! R
R-estimator of scale, 尺度R估计量8 Y$ h! n/ t( L3 K% k7 a% S
Retrospective study, 回顾性调查
( ~9 o, d, D0 x3 f6 g# VRidge trace, 岭迹
4 X6 v1 u# h7 U3 }5 ^" X5 g8 \8 XRidit analysis, Ridit分析
3 U1 C7 K) z; a+ A# Q3 ERotation, 旋转
2 q9 A' g' d% \ FRounding, 舍入
: y* _% h0 a! FRow, 行& }6 o: O2 Q+ w' `) K$ W
Row effects, 行效应
6 K1 | w Y% D) G9 c( W, A$ TRow factor, 行因素
9 M" K( q! L- E) i/ Z4 H: MRXC table, RXC表+ a5 J3 \- v, ?8 Y, X% F+ [ E2 u0 e
Sample, 样本9 H; E2 ]1 P( c0 }$ G, B f
Sample regression coefficient, 样本回归系数
+ C9 ~7 _1 o/ s8 s0 ^: Q+ nSample size, 样本量# D- c& F$ t5 C9 f( E
Sample standard deviation, 样本标准差/ d# I1 f/ @/ f( I
Sampling error, 抽样误差) ~9 ^: x% a) K% s) x1 R2 a
SAS(Statistical analysis system ), SAS统计软件包
- S. @7 |' o9 C1 t+ xScale, 尺度/量表9 R3 P' p. C7 q
Scatter diagram, 散点图$ p# K1 a0 f& u$ m; W8 _
Schematic plot, 示意图/简图7 t( u3 q. D: M0 V7 t4 E
Score test, 计分检验6 K+ t0 T; ?: h$ |. }$ O8 [
Screening, 筛检
/ e, F% u5 _8 W" [, S+ s: ISEASON, 季节分析 $ q9 x( t3 ~. O! x3 r: p
Second derivative, 二阶导数
: d4 _# ]1 p( USecond principal component, 第二主成分: z: E: L# a& y; {2 U# S, Z/ q
SEM (Structural equation modeling), 结构化方程模型
. w1 F- V4 j* `1 o, G3 fSemi-logarithmic graph, 半对数图
* Y. o0 Z- ?# s1 I% i& q, USemi-logarithmic paper, 半对数格纸
4 W! i3 }7 p, g9 z$ ~; jSensitivity curve, 敏感度曲线
4 ~" H4 R& M. _% Q; ], q LSequential analysis, 贯序分析
5 F/ {, @3 S6 h' O* k4 Q! }Sequential data set, 顺序数据集! N0 P4 x* `: a0 O4 @$ W3 |
Sequential design, 贯序设计
# `9 U' A; f; Y* n6 l6 P* vSequential method, 贯序法9 e2 H$ D3 Q$ Y
Sequential test, 贯序检验法
$ `% h- H9 k9 ?: n" H, _Serial tests, 系列试验1 E H+ G0 _1 B6 ]! R& d
Short-cut method, 简捷法 ) r. o$ A! |# o4 l" p9 c
Sigmoid curve, S形曲线; k; {# X3 g1 Q8 y
Sign function, 正负号函数7 `# T, U/ k" g/ Q# r- r2 X, Y7 Q
Sign test, 符号检验
$ e# z6 G& Q+ A `) {* q4 a4 |Signed rank, 符号秩9 g, |/ \2 p% c1 `- L* w: z
Significance test, 显著性检验' k$ U* \. R* X. n3 E, M
Significant figure, 有效数字- q$ I6 y' f& }- t9 a
Simple cluster sampling, 简单整群抽样
) }2 b, P+ c( c# A. k+ ]3 J$ RSimple correlation, 简单相关
8 p* I( z) p1 B5 z& n; g) F/ ]( RSimple random sampling, 简单随机抽样
. ?6 S9 o3 H0 R7 I* kSimple regression, 简单回归
' n6 R& K# M' Esimple table, 简单表4 B2 m6 y; o1 u% K n- R
Sine estimator, 正弦估计量
; A: l$ B, K; U1 ]Single-valued estimate, 单值估计
9 ?8 \2 e5 {2 G6 A& P- F" r1 X) lSingular matrix, 奇异矩阵
/ _; @, Q* X o0 Q0 t; N0 M0 z, @Skewed distribution, 偏斜分布! V/ r3 o+ `2 V( O" Z8 |
Skewness, 偏度0 R' ^8 C* r$ R6 f1 s% I2 b3 T
Slash distribution, 斜线分布
+ A* ~& [' ^6 e+ l0 e. zSlope, 斜率
' j# A$ i& D) Z! x9 f. ~Smirnov test, 斯米尔诺夫检验! p& _5 M5 ?- }
Source of variation, 变异来源
+ c6 \( B3 s1 Q a" WSpearman rank correlation, 斯皮尔曼等级相关, |6 i$ X: R" r) R d% P3 }
Specific factor, 特殊因子
+ _ x: v# Z; Z! T0 e9 M! CSpecific factor variance, 特殊因子方差$ w% F3 n& F2 m
Spectra , 频谱
; _* N k) ^6 JSpherical distribution, 球型正态分布" n& s' L/ G" w0 U
Spread, 展布% Q O' z/ k9 r% O+ _0 R+ `
SPSS(Statistical package for the social science), SPSS统计软件包
. K$ E' \/ j$ ^- h1 {Spurious correlation, 假性相关+ ^: b; M" J. m( L
Square root transformation, 平方根变换
# }9 |4 T; q6 ?Stabilizing variance, 稳定方差% b: g. @! F0 v+ I% Y# x
Standard deviation, 标准差
# C$ b: F: D5 X' d: v. OStandard error, 标准误6 l0 @7 A# P8 a' F
Standard error of difference, 差别的标准误 R+ e7 ~' S% |) W, U: X; b- U
Standard error of estimate, 标准估计误差
_$ k/ n3 z6 L1 V" j! t' N1 J7 JStandard error of rate, 率的标准误# s+ k) A+ R9 _* U, k$ K
Standard normal distribution, 标准正态分布
/ x9 G4 s# P$ ]Standardization, 标准化
1 l9 U c H [& O* hStarting value, 起始值
' Q7 {0 B( a; p3 P& i2 J* d& iStatistic, 统计量
4 k' F' t1 r0 I% l+ r pStatistical control, 统计控制
/ i) C. _+ v5 Q- Y/ ]& aStatistical graph, 统计图
; ?. c* h7 N1 _$ ]9 j$ mStatistical inference, 统计推断9 L/ N3 o; Y' D. O
Statistical table, 统计表; R: d3 I% t4 L% j; C
Steepest descent, 最速下降法
" i7 r6 @2 P4 Q& ^6 ?: l0 OStem and leaf display, 茎叶图
( B6 {4 @2 O3 R- sStep factor, 步长因子
1 T d5 M8 a- H: Z7 W+ y1 uStepwise regression, 逐步回归/ r5 [: T! J5 O3 `7 d
Storage, 存
1 G) c$ O7 \, SStrata, 层（复数）
3 u5 M( F5 M! f* e- w" ]1 J( QStratified sampling, 分层抽样
3 a- i% U3 |, R; j+ @2 c( f% qStratified sampling, 分层抽样7 t# {0 S$ i( O( K: B5 j& H7 U
Strength, 强度
/ K0 E6 J1 Q- H! o- q2 X' ^Stringency, 严密性
& o# v" W; I6 g7 ?0 DStructural relationship, 结构关系
z, m k) V! v. Z g8 g: i* wStudentized residual, 学生化残差/t化残差0 F9 P; z/ F7 u0 P2 Q% n
Sub-class numbers, 次级组含量1 u" a" o1 Z3 Z2 u) k6 s
Subdividing, 分割% d) M& o, V+ {5 i
Sufficient statistic, 充分统计量* P) m+ {. r; \0 Z
Sum of products, 积和
; X: ^0 s& t( jSum of squares, 离差平方和
^0 W' u M/ ?Sum of squares about regression, 回归平方和
0 L& G* n5 [& t+ x( Y( _Sum of squares between groups, 组间平方和5 @6 `3 c. f/ q) G) O# `
Sum of squares of partial regression, 偏回归平方和# O6 p, Y9 z4 Z0 T" w+ g: E
Sure event, 必然事件
1 e: M9 E1 J8 [ z% hSurvey, 调查
+ q& d0 g, @7 e% X( PSurvival, 生存分析* p( V$ D! p% w6 q/ ^. ~' g
Survival rate, 生存率
' a9 G9 i2 z: W9 Q' U% ^' PSuspended root gram, 悬吊根图% ?, `& `& Z& P2 Q$ t
Symmetry, 对称! Z2 R, n. C. P3 |
Systematic error, 系统误差" g/ Q; O+ i0 b! j) D# G
Systematic sampling, 系统抽样$ K8 T8 u: P; [ [7 K5 ^
Tags, 标签' D+ @: ~2 T5 k& p l+ P* t
Tail area, 尾部面积, ~( j/ W5 x" s- {& N
Tail length, 尾长
) D; H6 x7 o' m0 ATail weight, 尾重6 A; \2 G. W$ {6 ]
Tangent line, 切线
( b$ x) h2 F9 P% D0 ZTarget distribution, 目标分布9 g8 O) }% [4 N4 Q
Taylor series, 泰勒级数
J. ~& X/ \ d6 f$ \3 X2 A# iTendency of dispersion, 离散趋势
8 `( [; P! B2 W2 ~6 n( S; n! _Testing of hypotheses, 假设检验! Z; J k3 G2 r" q ]- ~
Theoretical frequency, 理论频数
" ~2 n- H* Q% lTime series, 时间序列! `+ r& V- q7 i; m7 j+ X
Tolerance interval, 容忍区间
+ V! T% }; f. `0 p( y% r* |Tolerance lower limit, 容忍下限7 V* Z5 I: j1 {/ e' p: [
Tolerance upper limit, 容忍上限
; u3 [6 j; F6 O: H( OTorsion, 扰率( [; u' Q4 S$ s, s2 e/ a4 e! k8 e
Total sum of square, 总平方和
* W' y. w7 O. y+ pTotal variation, 总变异
1 ?7 C) b$ u& p! S) i. pTransformation, 转换) f; |; } O5 O
Treatment, 处理( r7 i$ g6 V) s8 i
Trend, 趋势! K* k" x' }) m. `
Trend of percentage, 百分比趋势' @& U7 h: x8 W: H! _7 s) N8 S
Trial, 试验, C8 U7 h! T$ }: b: a! k
Trial and error method, 试错法+ S5 l+ Y$ F7 r$ Z }4 }
Tuning constant, 细调常数
, @+ k" }. L* q6 ?9 vTwo sided test, 双向检验
5 w. M& c6 H+ J `" Q* hTwo-stage least squares, 二阶最小平方
. K! r9 W' ]; QTwo-stage sampling, 二阶段抽样. z9 J* ~0 h+ M' b) H
Two-tailed test, 双侧检验: I2 Z; z# O& [% D; N' T, [6 U
Two-way analysis of variance, 双因素方差分析
% y, d1 C! E, t% c6 v' ]- p- @& vTwo-way table, 双向表
7 L* P+ }( m/ F1 T+ C5 kType I error, 一类错误/α错误* B% ~0 T+ f, \! o/ ]
Type II error, 二类错误/β错误 x% V/ f o& u0 }0 z" k
UMVU, 方差一致最小无偏估计简称4 a& [/ x+ U* s9 r. C( ?2 j
Unbiased estimate, 无偏估计, K l! X2 S6 {6 V4 ]) l
Unconstrained nonlinear regression , 无约束非线性回归9 y2 x' e$ I& C5 s4 U3 B2 _5 }1 \
Unequal subclass number, 不等次级组含量
9 t% N2 j0 g6 L! ]- a/ \) y( p6 vUngrouped data, 不分组资料
& o" n G4 ~5 C( tUniform coordinate, 均匀坐标
. }# `7 x( D/ s. x/ C& nUniform distribution, 均匀分布
8 E, r: [- S, O# m7 D) G' WUniformly minimum variance unbiased estimate, 方差一致最小无偏估计7 W8 B! V, C. v% `
Unit, 单元# v) S U/ ^3 T+ C$ Q
Unordered categories, 无序分类
2 T5 H4 Q( G# Z4 _; T) P) e1 b- [& WUpper limit, 上限$ ?7 {# m* l& ^: K% @
Upward rank, 升秩6 f2 A0 X; }7 g( b/ T
Vague concept, 模糊概念2 L d/ k% l& y; f6 j
Validity, 有效性- L, K- e# s$ J' t7 \; z' V
VARCOMP (Variance component estimation), 方差元素估计* _% L6 N! r# I3 @3 ~, Z. _; |
Variability, 变异性
" r4 H& B# v! J& l' gVariable, 变量
/ Z( j8 i0 h5 ^4 E) I8 K( {Variance, 方差
5 W+ M1 O) M) l, ]8 e- RVariation, 变异
9 D$ u9 C7 H" B4 _2 y+ tVarimax orthogonal rotation, 方差最大正交旋转
, u5 Z% y# d9 ~, x% |+ yVolume of distribution, 容积! k/ N( U' }) M% h6 U6 x
W test, W检验$ E. K$ v( ~/ Z, X+ a" T
Weibull distribution, 威布尔分布
# A9 V% \! x) Z; E, E: @Weight, 权数. U, [! n L+ g- S7 f- H2 C
Weighted Chi-square test, 加权卡方检验/Cochran检验1 Q1 [7 x& S) u" j( G
Weighted linear regression method, 加权直线回归
$ L& z# \0 J8 K$ [5 DWeighted mean, 加权平均数
6 x! |# R4 h1 Y( Z, {$ JWeighted mean square, 加权平均方差
" Z0 j6 Z4 Q+ N! J* OWeighted sum of square, 加权平方和
. v6 U. s' m1 f; \Weighting coefficient, 权重系数
" x- K! ?6 M8 h8 x% F: VWeighting method, 加权法
: c9 V4 z. n" ~0 V" B$ o( G1 W- EW-estimation, W估计量, [% g1 k- e1 R9 d+ D
W-estimation of location, 位置W估计量. Z$ d7 W- a! k8 M6 Y# q3 F
Width, 宽度
7 K! ~2 m9 ?; N6 |Wilcoxon paired test, 威斯康星配对法/配对符号秩和检验) b) O( p& G8 `0 B9 n% P, e
Wild point, 野点/狂点, e8 A2 m8 R' S: N6 I0 L+ A
Wild value, 野值/狂值
' r* V$ q! v8 xWinsorized mean, 缩尾均值
! C, E* ?2 e2 ~+ bWithdraw, 失访 + Q6 A9 e6 ?/ L$ `" z4 S" ^. ~/ R
Youden's index, 尤登指数
# v6 Q1 I! a- k6 i# K; G. XZ test, Z检验
9 y0 y) @/ M* `( l$ S3 ]Zero correlation, 零相关
- V( e$ s# H) G4 }1 lZ-transformation, Z变换 |
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发表于 2009-1-6 22:05
